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Symeon Chatzinotas

Publications and source records attributed to Symeon Chatzinotas.

At least 181 records · Page 10Linked to original sources

Diversity and Multiplexing in Quantum MIMO Channels

Characterization and exploitation of multiple channels between the transmitter and the receiver in multiple-input multiple-output (MIMO) communications brought a paradigm shift in classical communication systems. The techniques developed around MIMO communication systems not only brought unprecedented advancements in the communication rates but also substantially improved the reliability of communication, measured by low error rates. Here, we explore the same ideas in the paradigm of quantum MIMO communication. Specifically, we utilize approximate quantum cloning to transmit multiple copies of the same quantum state over a MIMO channel that incorporates crosstalk, losses, and depolarizing noise. With this strategy, we find an achievable tradeoff between the average fidelity and communication rate over this MIMO setup.

quant-ph↗

Near-Field Beamforming for Stacked Intelligent Metasurfaces-assisted MIMO Networks

Stacked intelligent metasurfaces (SIMs) have recently gained significant interest since they enable precoding in the wave domain that comes with increased processing capability and reduced energy consumption. The study of SIMs and high frequency propagation make the study of the performance in the near field of crucial importance. Hence, in this work, we focus on SIM-assisted multiuser multiple-input multiple-output (MIMO) systems operating in the near field region. To this end, we formulate the weighted sum rate maximisation problem in terms of the transmit power and the phase shifts of the SIM. By applying a block coordinate descent (BCD)-relied algorithm, numerical results show the enhanced performance of the SIM in the near field with respect to the far field.

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Physical Layer Aspects of Quantum Communications: A Survey

Quantum communication systems support unique applications in the form of distributed quantum computing, distributed quantum sensing, and several cryptographic protocols. The main enabler in these communication systems is an efficient infrastructure that is capable to transport unknown quantum states with high rate and fidelity. This feat requires a new approach to communication system design which efficiently exploits the available physical layer resources, while respecting the limitations and principles of quantum information. Despite the fundamental differences between the classic and quantum worlds, there exist universal communication concepts that may proven beneficial in quantum communication systems as well. In this survey, the distinctive aspects of physical layer quantum communications are highlighted in a attempt to draw commonalities and divergences between classic and quantum communications. More specifically, we begin by overviewing the quantum channels and use cases over diverse optical propagation media, shedding light on the concepts of crosstalk and interference. Subsequently, we survey quantum sources, detectors, channels and modulation techniques. More importantly, we discuss and analyze spatial multiplexing techniques, such as coherent control, multiplexing, diversity and MIMO. Finally, we identify synergies between the two communication technologies and grand open challenges that can be pivotal in the development of next-generation quantum communication systems.

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Enhancing Indoor and Outdoor THz Communications with Beyond Diagonal-IRS: Optimization and Performance Analysis

This work investigates the application of Beyond Diagonal Intelligent Reflective Surface (BD-IRS) to enhance THz downlink communication systems, operating in a hybrid: reflective and transmissive mode, to simultaneously provide services to indoor and outdoor users. We propose an optimization framework that jointly optimizes the beamforming vectors and phase shifts in the hybrid reflective/transmissive mode, aiming to maximize the system sum rate. To tackle the challenges in solving the joint design problem, we employ the conjugate gradient method and propose an iterative algorithm that successively optimizes the hybrid beamforming vectors and the phase shifts. Through comprehensive numerical simulations, our findings demonstrate a significant improvement in rate when compared to existing benchmark schemes, including time- and frequency-divided approaches, by approximately $30.5\%$ and $69.9\%$ respectively and even outperforms the STAR-IRS system by $76.99\%$. This underscores the significant influence of IRS elements on system performance relative to that of base station antennas, highlighting their pivotal role in advancing the communication system efficacy.

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Interference analysis of Positioning Reference Signals in 5G NTN

Accurate asset localization holds paramount importance across various industries, ranging from transportation management to search and rescue operations. In scenarios where traditional positioning equations cannot be adequately solved due to limited measurements obtained by the receiver, the utilization of Non-Terrestrial Networks (NTN) based on Low Earth Orbit (LEO) satellites can prove pivotal for precise positioning. The decision to employ NTN in lieu of conventional Global Navigation Satellite Systems (GNSS) is rooted in two key factors. Firstly, GNSS systems are susceptible to jamming and spoofing attacks, thereby compromising their reliability, where LEO satellites link budgets can benefit from a closer distances and the new mega constellations could offer more satellites in view than GNSS. Secondly, 5G service providers seek to reduce dependence on third-party services. Presently, the NTN operation necessitates a GNSS receiver within the User Equipment (UE), placing the service provider at the mercy of GNSS reliability. Consequently, when GNSS signals are unavailable in certain regions, NTN services are also rendered inaccessible.

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Emerging Technologies for 6G Non-Terrestrial-Networks: From Academia to Industrial Applications

Terrestrial networks form the fundamental infrastructure of modern communication systems, serving more than 4 billion users globally. However, terrestrial networks are facing a wide range of challenges, from coverage and reliability to interference and congestion. As the demands of the 6G era are expected to be much higher, it is crucial to address these challenges to ensure a robust and efficient communication infrastructure for the future. To address these problems, Non-terrestrial Network (NTN) has emerged to be a promising solution. NTNs are communication networks that leverage airborne (e.g., unmanned aerial vehicles) and spaceborne vehicles (e.g., satellites) to facilitate ultra-reliable communications and connectivity with high data rates and low latency over expansive regions. This article aims to provide a comprehensive survey on the utilization of network slicing, Artificial Intelligence/Machine Learning (AI/ML), and Open Radio Access Network (ORAN) to address diverse challenges of NTNs from the perspectives of both academia and industry. Particularly, we first provide an in-depth tutorial on NTN and the key enabling technologies including network slicing, AI/ML, and ORAN. Then, we provide a comprehensive survey on how network slicing and AI/ML have been leveraged to overcome the challenges that NTNs are facing. Moreover, we present how ORAN can be utilized for NTNs. Finally, we highlight important challenges, open issues, and future research directions of NTN in the 6G era.

cs.NI↗

Non-Terrestrial Networks for 6G: Integrated, Intelligent and Ubiquitous Connectivity

Universal connectivity has been part of past and current generations of wireless systems, but as we approach 6G, the subject of social responsibility is being built as a core component. Given the advent of Non-Terrestrial Networks (NTN), reaching these goals will be much closer to realization than ever before. Owing to the benefits of NTN, the integration NTN and Terrestrial Networks (TN) is still infancy, where the past, the current and the future releases in the 3$^{\text{rd}}$ Generation Partnership Project (3GPP) provide guidelines to adopt a successfully co-existence/integration of TN and NTN. Therefore, in this article, we have illustrated through 3GPP guidelines, on how NTN and TN can effectively be integrated. Moreover, the role of beamforming and Artificial Intelligence (AI) algorithms is highlighted to achieve this integration. Finally the usefulness of integrating NTN and TN is validated through experimental analysis.

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Efficient Transmission Scheme for LEO Satellite-Based NB-IoT: A Data-Driven Perspective

This study analyses the medium access control (MAC) layer aspects of a low-Earth-orbit (LEO) satellite-based Internet of Things (IoT) network. A transmission scheme based on change detection is proposed to accommodate more users within the network and improve energy efficiency. Machine learning (ML) algorithms are also proposed to reduce the payload size by leveraging the correlation among the sensed parameters. Real-world data from an IoT testbed deployed for a smart city application is utilised to analyse the performance regarding collision probability, effective data received and average battery lifetime. The findings reveal that the traffic pattern, post-implementation of the proposed scheme, differs from the commonly assumed Poisson traffic, thus proving the effectiveness of having IoT data from actual deployment. It is demonstrated that the transmission scheme facilitates accommodating more devices while targeting a specific collision probability. Considering the link budget for a direct access NB-IoT scenario, more data is effectively offloaded to the server within the limited visibility of LEO satellites. The average battery lifetimes are also demonstrated to increase by many folds by using the proposed access schemes and ML algorithms.

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Demonstration of Safe Electromagnetic Radiation Emitted by 5G Active Antenna Systems

The careful planning and safe deployment of 5G technologies will bring enormous benefits to society and the economy. Higher frequency, beamforming, and small-cells are key technologies that will provide unmatched throughput and seamless connectivity to 5G users. Superficial knowledge of these technologies has raised concerns among the general public about the harmful effects of radiation. Several standardization bodies are active to put limits on the emissions which are based on a defined set of radiation measurement methodologies. However, due to the peculiarity of 5G such as dynamicity of the beams, network densification, Time Division Duplexing mode of operation, etc, using existing EMF measurement methods may provide inaccurate results. In this context, we discuss our experimental studies aimed towards the measurement of radiation caused by beam-based transmissions from a 5G base station equipped with an Active Antenna System(AAS). We elaborate on the shortcomings of current measurement methodologies and address several open questions. Next, we demonstrate that using user-specific downlink beamforming, not only better performance is achieved compared to non-beamformed downlink, but also the radiation in the vicinity of the intended user is significantly decreased. Further, we show that under weak reception conditions, an uplink transmission can cause significantly high radiation in the vicinity of the user equipment. We believe that our work will help in clearing several misleading concepts about the 5G EMF radiation effects. We conclude the work by providing guidelines to improve the methodology of EMF measurement by considering the spatiotemporal dynamicity of the 5G transmission.

cs.ET↗

Beyond Diagonal RIS-Aided Networks: Performance Analysis and Sectorization Tradeoff

Reconfigurable intelligent surfaces (RISs) have emerged as a spectrum- and energy-efficient technology to enhance the coverage of wireless communications within the upcoming 6G networks. Recently, novel extensions of this technology, referred to as multi-sector beyond diagonal RIS (BD-RIS), have been proposed, where the configurable elements are divided into $L$ sectors $(L \geq 2)$ and arranged as a polygon prism, with each sector covering $1/L$ space. This paper presents a performance analysis of a multi-user communication system assisted by a multi-sector BD-RIS operating in time-switching (TS) mode. Specifically, we derive closed-form expressions for the moment-generating function (MGF), probability density function (PDF), and cumulative density function (CDF) of the signal-to-noise ratio (SNR) per user. Furthermore, closed-form expressions for the outage probability, achievable spectral and energy efficiency, symbol error probability, and diversity order for the proposed system model are derived. Moreover, a comparison is performed with the simultaneously transmitting and reflecting (STAR)-RISs, a special case of multi-sector BD-RIS with two sectors. Our analysis shows that for a fixed number of elements, increasing the sectors improves outage performance at the expense of reduced diversity order compared to STAR-RIS. This trade-off is influenced by the Rician factors of the cascaded channel and the number of configurable elements per sector. However, this superiority in slope is observed at outage probability values below $10^{-5}$, which remains below practical operating ranges of communication systems. Additionally, simulations are provided to validate the accuracy of our theoretical analyses showing a notable $182\%$ increase in spectral efficiency and a $238\%$ increase in energy efficiency when transitioning from a 2-sector to a 6-sector configuration.

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Achievable Rate Optimization for Large Stacked Intelligent Metasurfaces Based on Statistical CSI

Stacked intelligent metasurface (SIM) is an emerging design that consists of multiple layers of metasurfaces. A SIM enables holographic multiple-input multiple-output (HMIMO) precoding in the wave domain, which results in the reduction of energy consumption and hardware cost. On the ground of multiuser beamforming, this letter focuses on the downlink achievable rate and its maximization. Contrary to previous works on multiuser SIM, we consider statistical channel state information (CSI) as opposed to instantaneous CSI to overcome challenges such as large overhead. Also, we examine the performance of large surfaces. We apply an alternating optimization (AO) algorithm regarding the phases of the SIM and the allocated transmit power. Simulations illustrate the performance of the considered large SIM-assisted design as well as the comparison between different CSI considerations.

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A Deep-NN Beamforming Approach for Dual Function Radar-Communication THz UAV

In this paper, we consider a scenario with one UAV equipped with a ULA, which sends combined information and sensing signals to communicate with multiple GBS and, at the same time, senses potential targets placed within an interested area on the ground. We aim to jointly design the transmit beamforming with the GBS association to optimize communication performance while ensuring high sensing accuracy. We propose a predictive beamforming framework based on a dual DNN solution to solve the formulated nonconvex optimization problem. A first DNN is trained to produce the required beamforming matrix for any point of the UAV flying area in a reduced time compared to state-of-the-art beamforming optimizers. A second DNN is trained to learn the optimal mapping from the input features, power, and EIRP constraints to the GBS association decision. Finally, we provide an extensive simulation analysis to corroborate the proposed approach and show the benefits of EIRP, SINR performance and computational speed.

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An Experimental Study of C-Band Channel Model in Integrated LEO Satellite and Terrestrial Systems

This paper studies the channel model for the integrated satellite-terrestrial networks operating at C-band under deployment in dense urban and rural areas. Particularly, the interference channel from the low-earth-orbit (LEO) satellite to the dense urban area is analyzed carefully under the impact of the environment's characteristics, i.e., the building density, building height, and the elevation angle. Subsequently, the experimental results show the strong relationships between these characteristics and the channel gain loss. Especially, the functions of channel gain loss are obtained by utilizing the model-fitting approach that can be used as the basis for studying future works of integration of satellite and terrestrial networks (ISTNs).

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On User Association in Large-Scale Heterogeneous LEO Satellite Network

In this paper, we investigate the performance of large-scale heterogeneous low Earth orbit (LEO) satellite networks in the context of three association schemes. In contrast to existing studies, where single-tier LEO satellite-based network deployments are considered, the developed framework captures the heterogeneous nature of real-world satellite network deployments. More specifically, we propose an analytical framework to evaluate the performance of multi-tier LEO satellite-based networks, where the locations of LEO satellites are approximated as points of independent Poisson point processes, with different density, transmit power, and altitude. We propose three association schemes for the considered network topology based on: 1) the Euclidean distance, 2) the average received power, and 3) a random selection. By using stochastic geometry tools, analytical expressions for the association probability, the downlink coverage probability, as well as the spectral efficiency are derived for each association scheme, where the interference is considered. Moreover, we assess the achieved network performance under several different fading environments, including low, typical, and severe fading conditions, namely non-fading, shadowed-Rician and Rayleigh fading channels, respectively. Our results reveal the impact of fading channels on the coverage probability, and illustrate that the average power-based association scheme outperforms in terms of achieved coverage and spectral efficiency performance against the other two association policies. Furthermore, we highlight the impact of the proposed association schemes and the network topology on the optimal number of LEO satellites, providing guidance for the planning of multi-tier LEO satellite-based networks in order to enhance network performance.

cs.ET↗

Achievable Rate Optimization for Stacked Intelligent Metasurface-Assisted Holographic MIMO Communications

Stacked intelligent metasurfaces (SIM) is a revolutionary technology, which can outperform its single-layer counterparts by performing advanced signal processing relying on wave propagation. In this work, we exploit SIM to enable transmit precoding and receiver combining in holographic multiple-input multiple-output (HMIMO) communications, and we study the achievable rate by formulating a joint optimization problem of the SIM phase shifts at both sides of the transceiver and the covariance matrix of the transmitted signal. Notably, we propose its solution by means of an iterative optimization algorithm that relies on the projected gradient method, and accounts for all optimization parameters simultaneously. We also obtain the step size guaranteeing the convergence of the proposed algorithm. Simulation results provide fundamental insights such the performance improvements compared to the single-RIS counterpart and conventional MIMO system. Remarkably, the proposed algorithm results in the same achievable rate as the alternating optimization (AO) benchmark but with a less number of iterations.

cs.IT↗

Optimizing Satellite Network Infrastructure: A Joint Approach to Gateway Placement and Routing

Satellite constellation systems are becoming more attractive to provide communication services worldwide, especially in areas without network connectivity. While optimizing satellite gateway placement is crucial for operators to minimize deployment and operating costs, reducing the number of gateways may require more inter-satellite link hops to reach the ground network, thereby increasing latency. Therefore, it is of significant importance to develop a framework that optimizes gateway placement, dynamic routing, and flow management in inter-satellite links to enhance network performance. To this end, we model an optimization problem as a mixed-integer problem with a cost function combining the number of gateways, flow allocation, and traffic latency, allowing satellite operators to set priorities based on their policies. Our simulation results indicate that the proposed approach effectively reduces the number of active gateways by selecting their most appropriate locations while balancing the trade-off between the number of gateways and traffic latency. Furthermore, we demonstrate the impact of different weights in the cost function on performance through comparative analysis.

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STAR-RIS-Assisted Communication Radar Coexistence: Analysis and Optimization

Integrated sensing and communication (ISAC) is expected to play a prominent role among emerging technologies in future wireless communications. In particular, a communication radar coexistence system is degraded significantly by mutual interference. In this work, given the advantages of promising reconfigurable intelligent surface (RIS), we propose a simultaneously transmitting and reflecting RIS (STAR-RIS)-assisted radar coexistence system where a STAR-RIS is introduced to improve the communication performance while suppressing the mutual interference and providing full space coverage. Based on the realistic conditions of correlated fading, and the presence of multiple user equipments (UEs) at both sides of the RIS, we derive the achievable rates at the radar and the communication receiver side in closed forms in terms of statistical channel state information (CSI). Next, we perform alternating optimization (AO) for optimizing the STAR-RIS and the radar beamforming. Regarding the former, we optimize the amplitudes and phase shifts of the STAR-RIS through a projected gradient ascent algorithm (PGAM) simultaneously with respect to the amplitudes and phase shifts of the surface for both energy splitting (ES) and mode switching (MS) operation protocols. The proposed optimization saves enough overhead since it can be performed every several coherence intervals. This property is particularly beneficial compared to reflecting-only RIS because a STAR-RIS includes the double number of variables, which require increased overhead. Finally, simulation results illustrate how the proposed architecture outperforms the conventional RIS counterpart, and show how the various parameters affect the performance. Moreover, a benchmark full instantaneous CSI (I-CSI) based design is provided and shown to result in higher sum-rate but also in large overhead associated with complexity.

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Emerging NGSO Constellations: Spectral Coexistence with GSO Satellite Communication Systems

Global communications have undergone a paradigm shift with the rapid expansion of low-earth orbit (LEO) satellite constellations, offering a new space era of reduced latency and ubiquitous, high-speed broadband internet access. However, the fast developments in LEO orbits pose significant challenges, particularly the coexistence with geostationary earth orbit (GEO) satellite systems. This article presents an overview of the regulatory aspects that cover the spectrum sharing in the bands allocated to the Fixed Satellite Service between geostationary networks (GSO) and non-geostationary systems (NGSO), as well as the main interference mitigation techniques for their coexistence. Our work highlights the increased potential for inter-system interference. It explores the regulatory landscape following the World Radio Conference (WRC-23). We discuss the different interference management strategies proposed for the GSO-NGSO spectral coexistence, including on-board and ground-based approaches and more advanced mitigation techniques based on beamforming. Moving onto operational aspects related to the sharing of spectrum, we introduce recent work on interference detection, identification, and mitigation and provide our vision of the emerging role of artificial intelligence (AI) in the aforementioned tasks.

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